Lightweight Word-Level Confidence Estimation for Neural Interactive Translation Prediction
نویسنده
چکیده
In neural interactive translation prediction, a system provides translation suggestions (“auto-complete” functionality) for human translators. These translation suggestions may be rejected by the translator in predictable ways; being able to estimate confidence in the quality of translation suggestions could be useful in providing additional information for users of the system. We show that a very small set of features (which are already generated as byproducts of the process of translation prediction) can be used in a simple model to estimate confidence for interactive translation
منابع مشابه
Application of Word-Level Confidence Measures in Interactive Statistical Machine Translation
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تاریخ انتشار 2018